When called as a program from the command line, the following form is used:

python timeit.py [-n N] [-r N] [-s S] [-t] [-c] [-h] [statement ...]

where the following options are understood:

-n N/--number=N

how many times to execute 'statement'

-r N/--repeat=N

how many times to repeat the timer (default 3)

-s S/--setup=S

statement to be executed once initially (default
'pass')

-t/--time

use time.time()
(default on all platforms but Windows)

-c/--clock

use time.clock() (default on Windows)

-v/--verbose

print raw timing results; repeat for more digits
precision

-h/--help

print a short usage message and exit

A multi-line statement may be given by specifying each line as a
separate statement argument; indented lines are possible by enclosing
an argument in quotes and using leading spaces. Multiple
-s options are treated similarly.

If -n is not given, a suitable number of loops is
calculated by trying successive powers of 10 until the total time is
at least 0.2 seconds.

The default timer function is platform dependent. On Windows,
time.clock() has microsecond granularity but
time.time()'s granularity is 1/60th of a second; on Unix,
time.clock() has 1/100th of a second granularity and
time.time() is much more precise. On either platform, the
default timer functions measure wall clock time, not the CPU time.
This means that other processes running on the same computer may
interfere with the timing. The best thing to do when accurate timing
is necessary is to repeat the timing a few times and use the best
time. The -r option is good for this; the default of 3
repetitions is probably enough in most cases. On Unix, you can use
time.clock() to measure CPU time.

Note:
There is a certain baseline overhead associated with executing a
pass statement. The code here doesn't try to hide it, but you
should be aware of it. The baseline overhead can be measured by
invoking the program without arguments.

The baseline overhead differs between Python versions! Also, to
fairly compare older Python versions to Python 2.3, you may want to
use Python's -O option for the older versions to avoid
timing SET_LINENO instructions.